Paper
18 March 2013 Tracking time interval changes of pulmonary nodules on follow-up 3D CT images via image-based risk score of lung cancer
Y. Kawata, N. Niki, H. Ohmatsu, M. Kusumoto, T. Tsuchida, K. Eguchi, M. Kaneko, N. Moriyama
Author Affiliations +
Proceedings Volume 8670, Medical Imaging 2013: Computer-Aided Diagnosis; 86700J (2013) https://doi.org/10.1117/12.2008113
Event: SPIE Medical Imaging, 2013, Lake Buena Vista (Orlando Area), Florida, United States
Abstract
In this paper, we present a computer-aided follow-up (CAF) scheme to support physicians to track interval changes of pulmonary nodules on three dimensional (3D) CT images and to decide the treatment strategies without making any under or over treatment. Our scheme involves analyzing CT histograms to evaluate the volumetric distribution of CT values within pulmonary nodules. A variational Bayesian mixture modeling framework translates the image-derived features into an image-based risk score for predicting the patient recurrence-free survival. Through applying our scheme to follow-up 3D CT images of pulmonary nodules, we demonstrate the potential usefulness of the CAF scheme which can provide the trajectories that can characterize time interval changes of pulmonary nodules.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Y. Kawata, N. Niki, H. Ohmatsu, M. Kusumoto, T. Tsuchida, K. Eguchi, M. Kaneko, and N. Moriyama "Tracking time interval changes of pulmonary nodules on follow-up 3D CT images via image-based risk score of lung cancer", Proc. SPIE 8670, Medical Imaging 2013: Computer-Aided Diagnosis, 86700J (18 March 2013); https://doi.org/10.1117/12.2008113
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KEYWORDS
Computed tomography

3D image processing

Lung cancer

Image segmentation

Cancer

Expectation maximization algorithms

Lung

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